Initial Results of Calibrating the Baron LIS-NOAH V2 Fully Distributed Hydrological Modeling System for the DMIP Elk River Basin
Because the OHD-based DMIP and DMIP-II programs offer very high quality long-term hydrometeorological datasets, the development of a calibration protocol for LN2 is relying in part on this resource. In particular, the Elk River basin near the Missouri-Oklahoma-Arkansas border is being used to benchmark an initial calibration effort. The effort is targeting a systematic approach in which (1) land-surface, overland flow, and subsurface flow algorithms are first calibrated for long-term observed stream inflow; (2) the baseflow/bucket component is calibrated using long-term observed baseflow; and finally (3) the channel routing is calibrated to improve hydrograph timing and peak flows. In each case, the non-linear PEST package is providing the optimization kernel. Spin-up, calibration, and validation time-periods are being chosen in order to isolate the observed data used for validation from that used for calibration.
Because such calibrations almost always require long-term datasets (order of a decade), the time scale of relatively rapid "greenhouse-gas-based" climate-change may potentially approach that same length, where hydrological forcing inputs are concerned (i.e. precipitation and temperature). This means that the need to perform repeated calibrations of most operational hydrological models can only increase if climate change intensifies. Hence, new strategies may have to be adopted whereby a nearly continual process of long-term calibration of operational models is under way in something of a "revolving door" fashion at operational centers.
This talk will report on the initial calibration results and also address in general terms the kind of strategies that may be needed for "quasi-continual recalibration" of a model such as LN2 under relatively rapid climate change scenarios.